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At least 451 records · Page 25

Exploring the Relationship of Microstructure and Conductivity in Metal Halide Perovskites via Active Learning-Driven Automated Scanning Probe Microscopy

Electronic transport and hysteresis in metal halide perovskites (MHPs) are key to the applications in photovoltaics, light emitting devices, and light and chemical sensors. These phenomena are strongly affected by the materials microstructure including grain boundaries, ferroic domain walls, and secondary phase inclusions. Here, we demonstrate an active machine learning framework for “driving” an automated scanning probe microscope (SPM) to discover the microstructures responsible for specific aspects of transport behavior in MHPs. In our setup, the microscope can discover the microstructural elements that maximize the onset of conduction, hysteresis, or any other characteristic that can be derived from a set of current–voltage spectra. Furthermore, this approach opens new opportunities for exploring the origins of materials functionality in complex materials by SPM and can be integrated with other characterization techniques either before (prior knowledge) or after (identification of locations of interest for detail studies) functional probing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of Dispersion Medium Composition and Ionomer Concentration on the Microstructure and Rheology of Fe–N–C Platinum Group Metal-free Catalyst Inks for Polymer Electrolyte Membrane Fuel Cells

In this paper, we present an investigation of the microstructure and rheological behavior of catalyst inks consisting of Fe–N–C platinum group metal-free catalysts and a perfluorosulfonic acid ionomer in a dispersion medium (DM) of water and 1-propanol ( n PA). The effects of the ionomer-to-catalyst (I/C) ratio and weight percentage of water (H 2 O %) in the DM on the ink microstructure were studied. Steady-shear and dynamic-oscillatory-shear rheology, in combination with synchrotron X-ray scattering, was utilized to understand interparticle interactions and the level of agglomeration of the inks. In the absence of the ionomer, the inks were significantly agglomerated, approaching a gel-like microstructure for catalyst concentrations as low as 2 wt %. The effect of H 2 O % in the DM on particle agglomeration was found to vary with particle concentration. In concentrated inks (≥2 wt % catalyst), increasing H 2 O % was found to increase agglomeration because of the hydrophobic nature of the catalysts. In dilute inks (<1 wt % catalyst), the trend was reversed with increasing H 2 O %, suggesting that electrostatic interactions are dominating the behavior. In inks with 5 wt % catalyst, the addition of an ionomer was found to significantly stabilize the catalyst against agglomeration. Maximum stability was observed at 0.35 I/C for all DM H 2 O % studied. At high ionomer concentrations (I/C > 0.35), interesting differences were observed between n PA-rich inks (H 2 O % ≤ 50%) and H 2 O-rich (82% H 2 O) inks. The n PA-rich inks remained predominantly stable—ink viscosity only weakly increased with I/C and the Newtonian behavior was maintained for I/C up to 0.9. In contrast, the H 2 O-rich inks exhibited a significant increase in viscoelasticity with increasing I/C, suggesting flocculation of the catalyst by the ionomer. These differences suggest that the nature of the interactions between the ionomer and catalyst is highly dependent on the H 2 O % in the DM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microstructural Evaluation of Phase Instability in Large Bandgap Metal Halide Perovskites

The optoelectronic performance of organic–inorganic halide perovskite (OIHP)-based devices has been improved in recent years. Particularly, solar cells fabricated using mixed-cations and mixed-halides have outperformed their single-cation and single-halide counterparts. Yet, a systematic evaluation of the microstructural behavior of mixed perovskites is missing despite their known composition-dependent photoinstability. Here, we explore microstructural inhomogeneity in (FAPbI 3 ) x (MAPbBr 3 ) 1– x using advanced scanning probe microscopy techniques. In this work, contact potential difference (CPD) maps measured by Kelvin probe force microscopy show an increased fraction of grains exhibiting a low CPD with flat topography as MAPbBr 3 concentration is increased. The higher portion of low CPD contributes to asymmetric CPD distribution curves. Chemical analysis reveals these grains being rich in MA, Pb, and I. The composition-dependent phase segregation upon illumination, reflected on the emergence of a low-energy peak emission in the original photoluminescence spectra, arises from the formation of such grains with flat topology. Bias-dependent piezo-response force microscopy measurements, in these grains, further confirm vigorous ion migration and cause a hysteretic piezo-response. Our results, therefore, provide insights into the microstructural evaluation of phase segregation and ion migration in OIHPs pointing toward process optimization as a mean to further enhance their optoelectronic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Redox-Induced Microstructure and Phase Dynamics in Nickel: Insights from In Situ Synchrotron X-ray Diffraction

Using in situ synchrotron X-ray diffraction, we interrogate the microstructural and phase evolution of polycrystalline nickel (Ni) during redox cycling in O 2 , H 2 , and H 2 O environments. Oxidation in O 2 promotes strong (111) texturing in both the NiO overlayer and the underlying Ni substrate. However, this crystallographic alignment is lost following reduction in H 2 and subsequent reoxidation, demonstrating irreversible microstructural changes. H 2 exposure leads to proton dissolution into the Ni lattice, triggering a localized phase transition from face-centered cubic (FCC) to hexagonal close-packed (HCP) Ni in hydrogen-saturated regions. In H 2 O-containing atmospheres, dissociative H 2 O adsorption produces protons that permeate the NiO layer, forming γ-NiOOH within the NiO lattice and HCP Ni beneath the NiO overlayer as protons accumulate. Kinetic analysis via the Johnson-Mehl-Avrami–Kolmogorov model uncovers distinct growth mechanisms: preoxidized Ni surfaces follow one-dimensional (1D) kinetics for NiO, γ-NiOOH, and HCP growth, whereas pristine Ni exhibits three-dimensional (3D) kinetics due to island-like nucleation and growth of NiO. Furthermore, these results highlight the critical interplay between H 2 O dissociation, hydrogen permeation, and redox-driven phase transformations, with practical implications in engineering nickel-based catalysts and hydrogen storage systems through controlled microstructural and phase evolution.

36 MATERIALS SCIENCE↗

Imaging grain microstructure in a model ceramic energy material with optically generated coherent acoustic phonons

Characterization of microstructure, chemistry and function of advanced energy materials remains a challenge for instrumentation science with tremendous opportunity for new discoveries. This active area of research is starting to make considerable strides with examples ranging from methodologies that employ bright X-rays, electron microscopy and optical spectroscopy. However, further development of instruments, capable of multimodal measurements, is necessary to fully reveal complex microstructure evolution in realistic environments and dynamical systems that are far from equilibrium. In this regard, laser-based instruments have a unique advantage as multiple measurement methodologies are easily combined into a single instrument using standard optics. A new pump-probe method that uses optically generated acoustic phonons is expanding standard optical characterization by providing depth resolved information. Here we report on a noteworthy extension of this pump-probe method to image grain microstructure in ceria. Rich information regarding the orientation of individual crystallites is obtained by monitoring acoustic phonon velocities and noting how the polarization of the probe beam influences the detected signal amplitude. When paired with other optical microscopies, this methodology will provide new perspectives for optical characterization of ceramic materials.

36 MATERIALS SCIENCE↗

Mutual modulation between surface chemistry and bulk microstructure within secondary particles of nickel-rich layered oxides

Abstract Surface lattice reconstruction is commonly observed in nickel-rich layered oxide battery cathode materials, causing unsatisfactory high-voltage cycling performance. However, the interplay of the surface chemistry and the bulk microstructure remains largely unexplored due to the intrinsic structural complexity and the lack of integrated diagnostic tools for a thorough investigation at complementary length scales. Herein, by combining nano-resolution X-ray probes in both soft and hard X-ray regimes, we demonstrate correlative surface chemical mapping and bulk microstructure imaging over a single charged LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) secondary particle. We reveal that the sub-particle regions with more micro cracks are associated with more severe surface degradation. A mechanism of mutual modulation between the surface chemistry and the bulk microstructure is formulated based on our experimental observations and finite element modeling. Such a surface-to-bulk reaction coupling effect is fundamentally important for the design of the next generation battery cathode materials.

25 ENERGY STORAGE↗

Learning two-phase microstructure evolution using neural operators and autoencoder architectures

Abstract Phase-field modeling is an effective but computationally expensive method for capturing the mesoscale morphological and microstructure evolution in materials. Hence, fast and generalizable surrogate models are needed to alleviate the cost of computationally taxing processes such as in optimization and design of materials. The intrinsic discontinuous nature of the physical phenomena incurred by the presence of sharp phase boundaries makes the training of the surrogate model cumbersome. We develop a framework that integrates a convolutional autoencoder architecture with a deep neural operator (DeepONet) to learn the dynamic evolution of a two-phase mixture and accelerate time-to-solution in predicting the microstructure evolution. We utilize the convolutional autoencoder to provide a compact representation of the microstructure data in a low-dimensional latent space. After DeepONet is trained in the latent space, it can be used to replace the high-fidelity phase-field numerical solver in interpolation tasks or to accelerate the numerical solver in extrapolation tasks.

36 MATERIALS SCIENCE↗

Microstructurally resolved electrochemical evolution of mechanical- and irradiation-induced damage in nuclear alloys

Abstract There is a need for high-throughput, scale-relevant, and direct electrochemical analysis to understand the corrosion behavior and sensitivity of nuclear materials that are exposed to extreme (high pressure, temperature, and radiation exposure) environments. We demonstrate the multi-scale, multi-modal application of scanning electrochemical cell microscopy (SECCM) to electrochemically profile corrosion alterations in nuclear alloys in a microstructurally resolved manner. Particularly, we identify that both mechanically deformed and irradiated microstructures show reduced charge-transfer resistance that leads to accelerated oxidation. We highlight that the effects of mechanical deformation and irradiation are synergistic, and may in fact, superimpose each other, with implications including general-, galvanic-, and/or irradiation-activated stress-corrosion cracking. Taken together, we highlight the ability of non-destructive, electrochemical interrogations to ascertain how microstructural alterations result in changes in the corrosion tendency of a nuclear alloy: knowledge which has implications to rank, qualify and examine alloys for use in nuclear construction applications.

Chen, Xin↗

Artificial intelligence inferred microstructural properties from voltage–capacity curves

Abstract The quantification of microstructural properties to optimize battery design and performance, to maintain product quality, or to track the degradation of LIBs remains expensive and slow when performed through currently used characterization approaches. In this paper, a convolution neural network-based deep learning approach (CNN) is reported to infer electrode microstructural properties from the inexpensive, easy to measure cell voltage versus capacity data. The developed framework combines two CNN models to balance the bias and variance of the overall predictions. As an example application, the method was demonstrated against porous electrode theory-generated voltage versus capacity plots. For the graphite|LiMn $$_2$$ 2 O $$_4$$ 4 chemistry, each voltage curve was parameterized as a function of the cathode microstructure tortuosity and area density, delivering CNN predictions of Bruggeman’s exponent and shape factor with 0.97 $$R^2$$ R 2 score within 2 s each, enabling to distinguish between different types of particle morphologies, anisotropies, and particle alignments. The developed neural network model can readily accelerate the processing-properties-performance and degradation characteristics of the existing and emerging LIB chemistries.

25 ENERGY STORAGE↗

Alloying effects on deformation induced microstructure evolution in copper

In this work, we investigated the effects of alloying elements on plastic deformation and microstructure evolution in polycrystalline copper (Cu) and Cu alloyed with 1 wt. % lead (Cu-1 %Pb). These materials were selected due to the size mismatch between Cu and Pb, with the latter forming precipitates at grain boundaries. Multi-modal characterization techniques, including neutron diffraction, electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM), along with finite element simulations were employed to study the deformation behavior across multiple length scales. While both Cu and Cu-1%Pb exhibited similar macroscale response and final deformation textures, both dislocation line profile analysis and TEM revealed increased dislocation density in deformed Cu-1%Pb specimens. The presence of lead precipitates also significantly affected local plastic deformation during compression, with their influence diminishing with increasing strain. These results demonstrate the complex relationships between alloying elements, plastic deformation, microstructural evolution, and material behavior under load. The insights gained from this multi-scale and multi-technique approach contribute to the fundamental understanding of microstructural evolution in immiscible alloys and are valuable for tailoring the properties of structural materials for specific engineering applications.

36 MATERIALS SCIENCE↗

High-energy ion beams generated with high efficiency using laser-driven 3D microstructures

Laser-driven ion acceleration in plasma is being proposed as a source of ion beams with a high peak current that can be useful in many fields of science and medicine. Using this method, high proton energies have been achieved by increasing the laser power and by using ultrathin (≤ 200 nm) foils. However, this approach is limited by survivability of the nanotargets to laser prepulses and by difficulty in controlling the plasma acceleration properties. Here, we introduce a new target platform using two-photon polymerization, 3D laser-printed “clone” microstructures with average densities lower than solid that are relatively insensitive to the laser prepulse. Two types of microstructured targets consisting of either a multilayered log-pile or a stochastic arrangement of one micron diameter wires are used. Both demonstrate a higher energy and higher yield proton acceleration compared to thin solid-density foil targets by the robust target normal sheath acceleration (TNSA) mechanism. We find that when such 10–20 μm thick structures are irradiated with a petawatt laser, protons with energies up to 110 MeV and a laser-to-proton conversion efficiency of ~ 10% are obtained. Our work suggests that such microstructures optimized for 60–200 MeV compact proton accelerators are promising for future radiotherapy and other applications.

Physics - Plasma physics↗

Hybrid microstructure of smectite clay gels revealed using neutron and synchrotron X-ray scattering

Aqueous suspensions of swelling clays display a nematic sol-gel transition at very low solid concentrations. The underlying microstructure of the gel has remained a point of contention since the time of Irving Langmuir and has been a major obstacle to fully realizing the potential of clays for practical applications. Here, we comprehensively probe the microstructure of a smectite clay suspension using ultra-small angle neutron/X-ray scattering and find that the nematic gel is structurally ordered and contains entities that are at least an order of magnitude larger than the individual particles. Complementary cryo-electron microscopy shows the presence of domains having particle-particle ordering responsible for nematic texture and regions of particle-particle aggregation responsible for gel-like behavior. We find that the smectic clay gels have a hybrid microstructure with co-existing repulsive nematic domains and attractive disordered domains.

36 MATERIALS SCIENCE↗

Part-scale evolution of fine-scale microstructural heterogeneity in solid-state additive manufacturing

Current solid-state additive manufacturing methods, refined through costly and time-consuming trial and error, have spurred interest in computational models that replicate material behavior under typical thermomechanical conditions (e.g., strain-rate ~ 102 s−1). These models, however, struggle to capture time-dependent microstructural evolution. In this work, Additive Friction-Stir Deposition (AFSD) is used as a representative case study for part-scale quantification of microstructure evolution at a fine spatial resolution (200 μm) by examining a liquid-nitrogen-cooled stop-action build via energy-dispersive X-ray diffraction coupled with a multi-channel detector. These results inform modeling efforts by linking process asymmetry to stored plastic strain, residual elastic strain, and texture development, and unlike current state-of-the-art characterization methods (e.g., EBSD or neutron diffraction), this approach provides both the spatial resolution and collection efficiency necessary to quantify fine-scale microstructural heterogeneity over large component volumes. As such, this technique provides essential validation data for computational models, e.g., crystal plasticity, enabling future prediction of heterogeneous behavior in AFSD and other additive manufacturing processes.

Franz, Cole [ORNL] (ORCID:0000000213465881)↗

The effects of aluminum concentration on the microstructural and electrochemical properties of lithium lanthanum zirconium oxide

Cubic lithium lanthanum zirconium oxide (Li 7-x Al x La 3 Zr 2 O 12 , LLZO) garnet has gained attention as a promising next-generation electrolyte for lithium batteries due to its high ionic conductivity and chemical stability with lithium metal. The high conductivity can be achieved through doping over a range of aluminum concentrations. In this study, we hot-pressed samples to achieve <2% nominal porosity with aluminum concentrations from x = 0.25–0.55 mol to understand the effect of aluminum on microstructure and electrochemistry. It was observed that beyond the aluminum solubility limit (x = ~0.40), resistive secondary phases formed at the grain boundaries. As a result, the percent grain boundary resistance increased from 17.6 to 41.2% for x = 0.25 and x = 0.55, respectively. Both the grain boundary and bulk activation energies remained relatively constant as the aluminum concentrations increased (~0.44 eV and ~0.39 eV, respectively). It was, therefore, surmised that the mobility term of the Nernst–Einstein equation was roughly independent of aluminum concentration and the major variable controlling bulk conductivity was the number of lithium charge carriers. As a result, as the aluminum concentration increased from x = 0.25 to x = 0.55 the bulk conductivity decreased from 0.56 to 0.15 mS cm -1 . Following these trends of increasing grain boundary resistance and decreasing bulk conductivity with increasing aluminum concentration, x = 0.25 had the highest total conductivity (0.46 mS cm -1 ). We demonstrated that aluminum concentration has a significant effect on the microstructure and electrochemical properties of LLZO. In conclusion, we believe this work could help understand how to link processing, microstructure, and electrochemical properties to guide the manufacturing of LLZO for use in solid-state batteries.

25 ENERGY STORAGE↗

Role of aggregates and microstructure of mixed-ionic–electronic-conductors on charge transport in electrochemical transistors

Synthetic efforts have delivered a library of organic mixed ionic–electronic conductors (OMIECs) with high performance in electrochemical transistors. The most promising materials are redox-active conjugated polymers with hydrophilic side chains that reach high transconductances in aqueous electrolytes due to volumetric electrochemical charging. Current approaches to improve transconductance and device stability focus mostly on materials chemistry including backbone and side chain design. However, other parameters such as the initial microstructure and microstructural rearrangements during electrochemical charging are equally important and are influenced by backbone and side chain chemistry. In this study, we employ a polymer system to investigate the fundamental electrochemical charging mechanisms of OMIECs. We couple in situ electronic charge transport measurements and spectroelectrochemistry with ex situ X-ray scattering electrochemical charging experiments and find that polymer chains planarize during electrochemical charging. Our work shows that the most effective conductivity modulation is related to electrochemical accessibility of well-ordered, interconnected aggregates that host high mobility electronic charge carriers. Electrochemical stress cycling induces microstructural changes, but we find that these aggregates can largely maintain order, providing insights on the structural stability and reversibility of electrochemical charging in these systems. Finally, this work shows the importance of material design for creating OMIECs that undergo structural rearrangements to accommodate ions and electronic charge carriers during which percolating networks are formed for efficient electronic charge transport.

36 MATERIALS SCIENCE↗

Imaging of voltage-controlled switching of magnetization in highly magnetostrictive epitaxial Fe–Ga microstructures

The magnetoelectric behavior of epitaxial Fe–Ga microstructures on top of a (001)-oriented PMN–PT piezoelectric substrate is imaged with magnetic X-ray microscopy. Additionally, the micron-scale strain distribution in PMN–PT is characterized by X-ray microdiffraction and examined with respect to the results of the Fe–Ga magnetoelectric switching. The magnetic reorientation of Fe–Ga is found to be strongly correlated with size, shape, and crystallographic orientation of the microstructures. In the case of square-shaped structures, size dictates the influence of the strain distribution on both the initialization of the ground state and on the magnetic reorientation during application of voltage. On the other hand, elliptical microstructures demonstrate completely different magnetic responses depending on the relative orientation of their long axis with respect to the crystallographic directions of the PMN–PT. This study demonstrates that engineering the behavior of highly magnetostrictive epitaxial microdevices is possible. It further elucidates that voltage-induced actuation can be largely tuned to achieve the desired type of magnetic switching ranging from vortex circulation reversal, domain wall motion, to a large rotation of magnetization. Because of the outstanding properties of the investigated material system, the reported findings are expected to be of great interest for the realization of next-generation energy-efficient magnetic memory and logic devices.

42 ENGINEERING↗

Microstructure of amide-functionalized polyethylenes determined by NMR relaxometry

Amidation of polyethylenes creates a range of amide-containing materials with enhanced properties, but the effect of these functional groups on the microstructure of these new materials is not known. Here we employ solid-state nuclear magnetic resonance (NMR) techniques to analyze the microstructure of amide-modified polyethylenes. While a decrease in crystallinity was observed with increasing amounts of functionalization, we found by measuring the chain mobility of the crystalline, amorphous, and interphasial regions of the polyethylenes with NMR relaxation techniques that the grafted amidyl groups partition into the rigid amorphous fraction (RAF) between the crystalline and amorphous regions. The chemical specificity of these NMR experiments creates precise assessments of the location of functional groups within the materials. Together, these insights into the microstructure and morphology of amide-containing polyethylenes lay a foundation for a deeper understanding of the structure and properties of functional polyolefins.

Haber, Shira [Lawrence Berkeley National Laborator↗

Damage initiation and evolution in Al-Si layered microstructures under shock loading conditions at atomic scales

Designing materials with microstructural features like multiphase interfaces have shown significant promise for usage in the next generation defense and nuclear applications. The dynamic response of these interfaces in extreme environments is observed to vary with the deformability of individual phases, which could subsequently alter the favored damage nucleation sites related to spall failure. Here, we investigate the role of spacing of interfaces in a nanocrystalline layered Aluminum-Silicon system on the shock wave propagation behavior, and microstructural and defect evolution using classical molecular dynamics simulations. The simulations are carried out with different hypothetical Al/Si microstructures including variations in the distribution of Si grains as layers in a nanocrystalline Al matrix. The molecular dynamics simulations suggest that spall failure is preferentially initiated at Al/Si interfaces. In addition, for the same system volume and same concentration of Si, a higher number of layers is marked by an increase in shock wave velocity and reduced resistance to spall failure.

36 MATERIALS SCIENCE↗